Parsing Methods for Context-Free Grammars

Abstract

The invention discloses a method for resolving a context-free grammar. In the conventional algorithm for resolving the context-free grammar, three methods, including rule first word index hash, state skipping first word inquiry hash and reusing of a resolving result of the same position and the same rule are introduced, and can be applied to a resolving process in any combination form. According to the resolving method, the resolving time of the context-free grammar can be reduced, and the resolving efficiency is increased. Due to the adoption of the rule first word index hush and reusing of a local resolving result, search of all nested sub-rules is avoided, and the search space is reduced; and meanwhile, the state skipping first word inquiry hash is adopted, so that a matched rule can be searched in a system by a small number of skips, even by one skip, and the resolving efficiency is increased greatly.

Description

technical field [0001] The invention relates to a method for parsing a context-free grammar. Background technique [0002] Context-free grammar (Content Free Grammar, CFG) is a formal grammar, which is defined as: For a grammar G[S], if each rule in the grammar rule set P is of the form A→α, A∈V N , α∈{V N ∪V T ) * , then the grammar G is a context-free grammar. According to the definition of context-free grammar, when applying the rule A → α in the derivation, A can always be replaced by the symbol string α without considering the context of the non-terminal symbol A. Therefore, the context-free grammar has strong enough expressive power and can It is used to define most computer programming languages ​​(C, XML, etc.), and is widely used in the field of natural language processing to describe the syntax and semantics of natural languages. [0003] Although context-free grammar has a wider description ability than another formal grammar regular language, its application...

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Problems solved by technology

[0017] In the above system process, the parsing process needs to search and match all possible grammar rules and nested sub-rules, and the search space is large, so it takes a long time, especially for a system consisting of tens of thousands of rules Complex grammar takes longer; at the same time, the current grammar analysis needs to traverse and match all possible jumps after each state. For the case of a large number of jumps, such as in natural language Thousands of possible quantifiers can be connected after the numerals, and the time overhead is considerable

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